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Updated: Aug 21, 2026

The Monoiodoacetate Model of Osteoarthritis Pain in the Mouse
Published on: May 16, 2016
Experimental models of osteoarthritis: Advances, limitations and rational selection for translational research
Jianxiong Shu1, Taiyuan Huang1, Zhaoran Wu1
1Department of Joint and Orthopedics, Orthopedic Center, Clinical Research Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Abstract:
Osteoarthritis (OA) is a complex degenerative joint disease driven by mechanical overload, inflammation, metabolic disorders, and aging. Despite substantial advances in basic and translational research, no disease-modifying OA drugs (DMOADs) have been approved for clinical use, largely due to the translational gap between preclinical experimental models and clinical practice. Experimental models are essential tools for investigating OA pathophysiology and evaluating therapeutic strategies, among which animal models play an irreplaceable role in recapitulating the in vivo joint environment. This review comprehensively evaluates current OA experimental models, with a focus on animal systems, including surgically induced structural instability, mechanically induced models, chemical induction approaches, metabolism-related models, spontaneous aging models, and genetically modified strains. We assess each model's advantages, limitations, and appropriate applications, clarifying their ability to reflect specific OA subtypes. Moreover, we summarize recent progress in in vitro platforms, ex vivo tissue explants, and emerging technologies such as organ-on-a-chip and organoid models, which provide complementary insights to animal models. This review aims to establish a rational model selection framework aligned with OA pathological features, thereby bridging the preclinical-clinical translational gap and facilitating the development of effective therapeutics.
The Translational Potential Of This Article:
This review systematically evaluates OA experimental models and analyzes their practical utility in translational research of different OA subtypes. It establishes a reasonable framework for model selection and describes how cutting-edge bioengineered platforms complement traditional in vitro and animal studies, providing a reference for improving the predictive reliability of preclinical research and advancing studies on personalized OA therapies.
Insights
Developing effective osteoarthritis (OA) treatments requires better experimental models. This review evaluates animal and in vitro models to bridge the gap between preclinical research and clinical applications for osteoarthritis therapies.
Area of Science:
- Biomedical research
- Translational science
- Osteoarthritis research
Background:
- Osteoarthritis (OA) is a complex joint disease with no approved disease-modifying drugs (DMOADs) due to a translational gap.
- Preclinical models are crucial for understanding OA and testing therapies, but their clinical relevance is often limited.
Purpose of the Study:
- To comprehensively review and evaluate current experimental models for osteoarthritis.
- To establish a rational framework for selecting appropriate OA models based on pathological features.
- To facilitate the development of effective OA therapeutics by bridging the preclinical-clinical translational gap.
Main Methods:
- Systematic evaluation of various animal models (surgical, mechanical, chemical, metabolic, aging, genetic).
- Assessment of in vitro platforms, ex vivo tissue explants, and emerging technologies (organ-on-a-chip, organoids).
- Analysis of model advantages, limitations, and applicability to specific OA subtypes.
Main Results:
- Current OA models have limitations in recapitulating the complexity of human disease.
- In vitro and bioengineered platforms offer complementary insights and can enhance predictive reliability.
- A framework for rational model selection is proposed to improve translational potential.
Conclusions:
- No single model perfectly replicates OA; a combination of approaches is often necessary.
- Improved model selection and utilization of novel platforms can accelerate the development of DMOADs.
- This review provides a reference for enhancing preclinical research reliability and advancing personalized OA therapies.

